FreeStatistics.org

Free Statistics

of Irreproducible Research!

Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_edabi.wasp
Title produced by softwareBivariate Explorative Data Analysis
Date of computationWed, 04 Nov 2009 13:39:02 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Nov/04/t125736719649nl1avkfrrxzbz.htm/, Retrieved Sat, 04 May 2024 14:38:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=53846, Retrieved Sat, 04 May 2024 14:38:58 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact139

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Explorative Data Analysis] [workshop 4,2,1] [2009-10-30 11:37:24] [35f0fff14d789f48983afb62e692bd0d]
- RMPD  [Partial Correlation] [workshop 5,2] [2009-10-30 14:17:43] [35f0fff14d789f48983afb62e692bd0d]
- RMPD      [Bivariate Explorative Data Analysis] [workshop 5,5] [2009-11-04 20:39:02] [2210215221105fab636491031ce54076] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
2,074
1,874
1,182
0,434
0,382
0,682
0,626
0,474
0,23
0,342
0,442
1,542
1,69
1,798
0,886
0,538
0,43
0,322
0,374
0,33
0,078
0,182
-0,026
0,774
0,974
0,774
0,066
-0,182
0,286
0,022
-0,082
0,022
-0,034
-0,434
-0,882
-0,678
-0,926
-1,326
-1,178
-0,814
-0,922
-0,918
-1,374
-1,874
-1,966
-2,162
-1,658
-0,254
0,142
-0,362
-0,346
-0,486
-0,03
0,21
0,518
0,318
-0,286
-0,942
-0,894
-0,146
-0,058
Dataseries Y:
Download CSV
Histogram 
1,056
0,956
0,348
0,221
0,548
0,748
0,629
0,056
-0,925
-1,487
-1,187
-0,387
0,04
-0,168
-1,106
-1,433
-1,025
-0,717
-0,244
-0,325
-0,598
-0,952
-0,744
-0,644
-0,444
0,556
-0,536
-0,163
-0,206
-0,117
0,137
0,183
0,164
0,064
-0,063
-0,317
-0,444
-0,144
0,283
0,694
1,102
1,048
1,129
1,029
0,721
0,467
0,413
0,259
0,213
0,267
-0,349
-0,084
-0,165
0,27
0,162
0,162
0,016
-0,003
0,224
0,651
0,713

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 4 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53846&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]4 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53846&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53846&T=0

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Model: Y[t] = c + b X[t] + e[t]
c0.00843225735059676
b-0.169514872133298

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 0.00843225735059676 \tabularnewline
b & -0.169514872133298 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53846&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]0.00843225735059676[/C][/ROW]
[ROW][C]b[/C][C]-0.169514872133298[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53846&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53846&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Model: Y[t] = c + b X[t] + e[t]
c0.00843225735059676
b-0.169514872133298






Descriptive Statistics about e[t]
# observations61
minimum-1.43745817108101
Q1-0.37720897779935
median0.0748792232763784
mean1.23799891672349e-16
Q30.318047876554677
maximum1.39914158745386

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 61 \tabularnewline
minimum & -1.43745817108101 \tabularnewline
Q1 & -0.37720897779935 \tabularnewline
median & 0.0748792232763784 \tabularnewline
mean & 1.23799891672349e-16 \tabularnewline
Q3 & 0.318047876554677 \tabularnewline
maximum & 1.39914158745386 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53846&T=2

[TABLE]
[ROW][C]Descriptive Statistics about e[t][/C][/ROW]
[ROW][C]# observations[/C][C]61[/C][/ROW]
[ROW][C]minimum[/C][C]-1.43745817108101[/C][/ROW]
[ROW][C]Q1[/C][C]-0.37720897779935[/C][/ROW]
[ROW][C]median[/C][C]0.0748792232763784[/C][/ROW]
[ROW][C]mean[/C][C]1.23799891672349e-16[/C][/ROW]
[ROW][C]Q3[/C][C]0.318047876554677[/C][/ROW]
[ROW][C]maximum[/C][C]1.39914158745386[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53846&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53846&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Descriptive Statistics about e[t]
# observations61
minimum-1.43745817108101
Q1-0.37720897779935
median0.0748792232763784
mean1.23799891672349e-16
Q30.318047876554677
maximum1.39914158745386


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 0 ; par2 = 36 ;
Parameters (R input):
par1 = 0 ; par2 = 36 ;
R code (references can be found in the software module):
par1 <- as.numeric(par1)
par2 <- as.numeric(par2)
x <- as.ts(x)
y <- as.ts(y)
mylm <- lm(y~x)
cbind(mylm$resid)
library(lattice)
bitmap(file='pic1.png')
plot(y,type='l',main='Run Sequence Plot of Y[t]',xlab='time or index',ylab='value')
grid()
dev.off()
bitmap(file='pic1a.png')
plot(x,type='l',main='Run Sequence Plot of X[t]',xlab='time or index',ylab='value')
grid()
dev.off()
bitmap(file='pic1b.png')
plot(x,y,main='Scatter Plot',xlab='X[t]',ylab='Y[t]')
grid()
dev.off()
bitmap(file='pic1c.png')
plot(mylm$resid,type='l',main='Run Sequence Plot of e[t]',xlab='time or index',ylab='value')
grid()
dev.off()
bitmap(file='pic2.png')
hist(mylm$resid,main='Histogram of e[t]')
dev.off()
bitmap(file='pic3.png')
if (par1 > 0)
{
densityplot(~mylm$resid,col='black',main=paste('Density Plot of e[t]   bw = ',par1),bw=par1)
} else {
densityplot(~mylm$resid,col='black',main='Density Plot of e[t]')
}
dev.off()
bitmap(file='pic4.png')
qqnorm(mylm$resid,main='QQ plot of e[t]')
qqline(mylm$resid)
grid()
dev.off()
if (par2 > 0)
{
bitmap(file='pic5.png')
acf(mylm$resid,lag.max=par2,main='Residual Autocorrelation Function')
grid()
dev.off()
}
summary(x)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Model: Y[t] = c + b X[t] + e[t]',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'c',1,TRUE)
a<-table.element(a,mylm$coeff[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'b',1,TRUE)
a<-table.element(a,mylm$coeff[[2]])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Descriptive Statistics about e[t]',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'# observations',header=TRUE)
a<-table.element(a,length(mylm$resid))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'minimum',header=TRUE)
a<-table.element(a,min(mylm$resid))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Q1',header=TRUE)
a<-table.element(a,quantile(mylm$resid,0.25))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'median',header=TRUE)
a<-table.element(a,median(mylm$resid))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'mean',header=TRUE)
a<-table.element(a,mean(mylm$resid))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Q3',header=TRUE)
a<-table.element(a,quantile(mylm$resid,0.75))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'maximum',header=TRUE)
a<-table.element(a,max(mylm$resid))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')